It is often necessary to assess a condition of a patient's tissue for diagnostic purposes or for evaluating the efficacy of a certain treatment on the patient. For instance, it is necessary to assess fibrosis in the livers of patients with chronic liver diseases. This is because liver fibrosis, which is characterized by the excessive accumulation of newly synthesized extracellular matrix in the liver, is the hallmark of most chronic liver diseases. Examples of such chronic liver diseases include chronic hepatitis B and C virus infections, alcoholic liver disease, non-alcoholic steatohepatitis (NASH) and autoimmune liver disease [1, 2]
To assess fibrosis in a tissue of a patient, biopsy (the extraction of a small tissue sample i.e. a biopsy tissue sample from the tissue of the patient) may first be performed, followed by an assessment of fibrosis in the tissue sample. However, since biopsy is an invasive technique, it creates physical discomfort for the patient and carries a certain degree of risk to the patient.
To date, non-invasive fibrosis assessment techniques (e.g. techniques [3]-[7]) have been developed. However, biopsy still remains the gold standard for fibrosis assessment. This is because while information such as inflammatory activity and collagen architecture may be provided via analysis of the tissue sample obtained via biopsy, such information still cannot be obtained via current non-invasive fibrosis assessment techniques. An example of a current non-invasive fibrosis assessment technique is the FibroScan which measures liver stiffness in a patient based on the velocity of a shear wave sent through the patient's liver and uses this measured liver stiffness as an indication of the extent of fibrosis in the patient's liver.
An objective way of assessing fibrosis in a tissue is to view fibrosis as a condition that progresses through many stages and to estimate the stage of fibrosis in the tissue. Currently, morphological approaches for such fibrosis assessments are usually semi-quantitative and rely mostly on user observations of architectural features in biopsy tissue samples. Examples of such approaches include the Metavir and Ishak methods [23-24] used for assessing liver fibrosis. As user observations of the architectural features in biopsy tissue samples are usually highly subjective due to inter- and intra-observer discrepancies [8-9], it is extremely difficult to track fine incremental fibrosis changes in a patient's tissue using the semi-quantitative approaches. Thus, the staging of fibrosis in these approaches is rather crude.
However, even among patients with the same disease at the same stage, there are variations in the clinical and functional states of these patients. Therefore, the ability to detect fine incremental fibrosis changes is important and will be useful in many applications. For example, such ability will be useful in the evaluation of treatment efficacies and justification of treatment strategies, especially with the development of more costly drugs for the treatment of various diseases (e.g. for the arrest/reversal of hepatic fibrosis). The ability to detect incremental fibrosis changes will also be useful for large-cohort hepatic fibrosis studies. Although current large-cohort hepatic fibrosis studies mostly focus on chronic hepatitis B and C, the epidemiologic landscape is changing. With the burgeoning obesity-related problems across the globe, an increasing populace is suffering from the metabolic syndrome which is associated with a liver disease called NASH that causes pericellular/perisinusoidal fibrosis. It would be beneficial to evaluate this liver disease using a large-cohort hepatic fibrosis study as well. Moreover, the concept of the pathogenesis of cirrhosis has evolved greatly in recent years. In particular, the International Liver Pathology Study Group has proposed replacing the term “cirrhosis” with “advanced chronic liver disease” as it recognizes that cirrhosis, which is usually viewed as a single stage (specifically, the last stage) of liver fibrosis, should instead be viewed as a progressive condition that evolves through more than one stage. In particular, it has been observed that as cirrhosis progresses, there is an exponential increase in the amount of fibrosis in the liver. Furthermore, it has been found that regression of cirrhosis with a reversal of fibrosis is possible. Thus, a pathophysiological staging of cirrhosis that incorporates clinical, histological and haemodynamic findings at different stages is preferable over the current one-stage view of cirrhosis.
As compared to semi-quantitative methods, fully quantitative methods rely less on highly subjective user observations and thus, have the potential to monitor finer incremental fibrosis changes over time [21]. Currently, fully quantitative methods quantifying liver histological information for the diagnosis and treatment of chronic-liver-disease (CLD) related fibrosis have been developed. These methods include image-based morphometric analysis methods, many of which require stained biopsy tissue samples. An example of a current image-based morphometric analysis method is the CPA method which uses a single measurement namely, the collagen percentage area (CPA) (i.e. percentage of collagen in the biopsy tissue sample), to assess fibrosis. This measurement is obtained using an acquired image of the tissue sample and is a quantitative measure reflecting the extent of extracellular matrix (ECM) deposition in the tissue [10-13] the tissue sample is obtained from.
Although using the CPA measurement allows the monitoring of fibrosis progression in research and clinical applications [10-13], such a measurement has its limitations. One of the most commonly reported limitations is that the CPA measurement is highly sensitive to the size of the biopsy tissue sample. For example, Paradis et al. [19] found that the coefficient of variation in CPA measurements obtained for 25 mm-long liver biopsy tissue samples is 45% whereas the coefficient of variation in CPA measurements obtained for 15 mm-long liver biopsy tissue samples is 55%.
In addition, it is more accurate to perform histo-pathological assessment of a tissue based on global architectural changes in the tissue than on a single measurement of fibrosis content in the tissue (such as the CPA) [20]. In fact, many of the recent findings have indicated that using the CPA alone to determine pathological scores for fibrosis in a liver biopsy tissue sample does not accurately assess the fibrosis in the sample [20-22]. Features like vascular shunts and liver cell regeneration are also critical for evaluation of advanced chronic liver diseases [22] but information about such features is also not included in the CPA measurement. With the advent of 3D imaging techniques, information about these features can potentially be obtained from 3D visualisation of biopsy tissue samples and an approach that better utilizes such information is desirable.
In view of the above, it will be extremely beneficial to have a robust and fully quantitative approach that can examine architectural changes in a tissue and detect fine incremental fibrosis changes in the tissue.